SRE: AI-Driven Automation & Azure Databricks

Socket.dev; Toronto; On-site; CAD 90,000 - 130,000; Full time

Job summary

RBC in Toronto is seeking a Site Resiliency Engineer to join the Production Support team, focusing on automating SRE solutions, monitoring improvements, and incident management. The role requires experience with Azure Databricks, OpenShift, Splunk, and PowerBI to enhance reliability across applications.

The position involves shift-based production support, on-call rotations with compensation, and ongoing learning to adopt automation and AI-driven reliability measures.

Qualifications

• Azure Databricks experience and ability to parse application logs.
• Knowledge of AI basics and how it applies to monitoring and reliability.
• Proficiency with PowerBI for dashboards and reporting.
• Comfort with after-hours work and on-call rotations.
• Ability to read and interpret logs from multiple applications.

Responsibilities

• Develop SRE solutions for monitoring, alerting, anomaly detection, self-healing and reliability testing.
• Implement monitoring and alerting, anomaly detection, self-healing and reliability testing for applications in scope.
• Drive automation initiatives to improve availability and performance.
• Create AI Agents and support automation deployments.
• Participate in incident and problem management for applications in scope.
• Pace continuous improvement by reviewing what went well and what didn’t.

Skills

Azure Databricks

Log analysis

PowerBI

AI basics

On-call readiness

Tools

Python

PowerShell

Bash

Splunk

OpenShift

Azure

Job description

RBC in Toronto is seeking a Site Resiliency Engineer to join the Production Support team, focusing on automating SRE solutions, monitoring improvements, and incident management. The role requires experience with Azure Databricks, OpenShift, Splunk, and PowerBI to enhance reliability across applications.

The position involves shift-based production support, on-call rotations with compensation, and ongoing learning to adopt automation and AI-driven reliability measures.